Search Results

One of the primary issues in the interpretation of vehicle impact response data, observed from vehicle crash test events, is coping with variability. This vehicle response inconsistency generally causes test results to be unpredictable and makes CAE test validation work difficult as well. This paper, considering the uncertain characteristics of vehicle impact events, has implemented a stochastic assessment of vehicle NCAP response variation through a CAE vehicle impact model, and it has accomplished the three primary study objectives as stated follows: 1) Identify the response variation causing factors stochastically from various structural and environmental factor candidates and quantify the degree of their influences on crash response, 2) Develop a methodology for interpreting the significance of the factor effects in conjunction with vehicle impact mechanics and physics, and 3) Implement a stochastic improvement of the vehicle NCAP responses and their repeatability

In a gasoline engine, the unswept in-cylinder residual gas and introduction of external EGR is one of the important means of controlling engine raw NOx emissions and improving part load fuel economy via reduction of pumping losses. Since the trapped in-cylinder Residual Gas Fraction (RGF, comprised of both internal, and external) significantly affects the combustion process, on-line diagnosis and monitoring of in-cylinder RGF is very important to the understanding of the in-cylinder dilution condition. This is critical during the combustion system development testing and calibration processes. However, on-line measurement of in-cylinder RGF is difficult and requires an expensive exhaust gas analyzer, making it impractical for every application. Other existing methods, based on measured intake and exhaust pressures (steady state or dynamic traces) to calculate gas mass flowrate across the cylinder ports, provide a fast and economical solution to this problem.

This paper reports on DaimlerChrysler's participation in the Ad Hoc Diesel Fuels Test Program. This program was initiated by the U.S. Department of Energy and included major U.S. auto makers, major U.S. oil companies, and the Department of Energy. The purpose of this program was to identify diesel fuels and fuel properties that could facilitate the successful use of compression ignition engines in passenger cars and light-duty trucks in the United States at Tier 2 and LEV II tailpipe emissions standards. This portion of the program focused on minimizing engine-out particulates and NOx by using selected fuels, (not a matrix of fuel properties,) in steady state dynamometer tests on a modern, direct injection, common rail diesel engine.

The durability of fuel tank straps is essential for vehicle safety. Extensive physical tests are conducted to verify designs for durability. Due to the complexity of the loads and the fuel-to-tank interaction, computer-aided-engineering (CAE) simulation has had limited application in this area. This paper presents a CAE method for fuel tank strap durability prediction. It discusses the analytical loads, modeling of fuel-to-tank interaction, dynamic analysis methods, and fatigue analysis methods. Analysis results are compared to physical test results. This method can be used in either a fuel-tank-system model or a full vehicle model. It can give directional design guidance for fuel tank strap durability in the early stages of product development to reduce vehicle development costs.

Cam-phasing is increasingly considered as a feasible Variable Valve Timing (VVT) technology for production engines. Additional independent control variables in a dual-independent VVT engine increase the complexity of the system, and achieving its full benefit depends critically on devising an optimum control strategy. A traditional approach relying on hardware experiments to generate set-point maps for all independent control variables leads to an exponential increase in the number of required tests and prohibitive cost. Instead, this work formulates the task of defining actuator set-points as an optimization problem. In our previous study, an optimization framework was developed and demonstrated with the objective of maximizing torque at full load. This study extends the technique and uses the optimization framework to minimize fuel consumption of a VVT engine at part load.

Computer applications have been widely used to assist product design. The successes and sophistication of computer aided engineering (CAE) techniques are respectfully recognized in this field. CAE applications in the manufacturing area however are still developing, although the manufacturing community is increasingly starting to pay attentions to computer simulations in its daily workings. This paper will briefly introduce some of these applications and promote awareness of computer simulations in manufacturing area. It contains four main sections: finite element analysis (FEA) in machining fixture design, FEA applications in component assembly, machining process simulations and machining vibrations in the milling operation. Each section comes with a practical case study, potential benefits are identified and conclusions are presented by using an integrated design and analysis approach.

Vehicle design and packaging is a repetitive and tedious process that involves frequent engineering and design changes. To improve design efficiency, a standard naming vehicle design methodology is proposed in this paper. For the geometric or the functional object used in the vehicle context, a standard name is assigned and also used as a unique object feature through its life cycle. With the proposed standard naming design methodology, the engineering knowledge can be efficiently embedded into the CAD design, and hence, vehicle design can be executed in a more automated fashion. Work case of the standard naming design methodology is illustrated by a vehicle design and packaging application using CATIA V5.

The Automotive Industry/Government Emissions Research CRADA (AIGER) has been working to develop a new methodology for the direct determination of nonmethane hydrocarbons (DNMHC) in vehicle testing. This new measurement technique avoids the need for subtraction of a separately determined methane value from the total hydrocarbon measurement as is presently required by the Code of Federal Regulations. This paper will cover the historical aspects of the development program, which was initiated in 1993 and concluded in 2002. A fast, gas chromatographic (GC) column technology was selected and developed for the measurement of the nonmethane hydrocarbons directly, without any interference or correction being caused by the co-presence of sample methane. This new methodology chromatographically separates the methane from the nonmethane hydrocarbons, and then measures both the methane and the backflushed, total nonmethane hydrocarbons using standard flame ionization detection (FID).

With the adoption of the California Low-Emission Vehicle Regulations and the associated lower emission standards such as LEV (Low-Emission Vehicle in 1990), ULEV (Ultra-Low-Emission Vehicle), and LEV II (1998 with SULEV-Super Ultra Low Emission Vehicle), concerns were raised by emissions researchers over the accuracy and reliability of collecting and analyzing emissions measurements at such low levels. The primary concerns were water condensation, optimizing dilution ratios, and elimination of background contamination. These concerns prompted a multi-year research program looking at several new sampling techniques. This paper will describe the cooperative research conducted into one of these new technologies, namely the Bag Mini-Diluter (BMD) and Direct Vehicle Exhaust (DVE) Volume system.

Exhaust durability is an important measure of quality, which can be predicted using CAE with accurate mount loads. This paper proposes an innovative method to calculate these loads from measured mount accelerations. A Chrysler vehicle was instrumented with accelerometers at both ends of its four exhaust mounts. The vehicle was tested at various durability routes or events at DaimlerChrysler Proving Grounds. These measured accelerations were integrated to obtain their velocities and displacements. The differences in velocities and displacements at each mount were multiplied by its damping and stiffness rates to obtain the mount load. The calculation was conducted for all three translational directions and for all events. The calculated mount loads are shown within reasonable range. Along with CAE, it is suggested to explore this method for exhaust durability development.

This paper describes a lightweight magnesium intensive automobile body structure concept developed at DaimlerChrysler to support a high fuel-efficiency vehicle project. This body structure resulted in more than 40% weight reduction over a conventional steel structure while achieving significantly improved structural performance as evaluated through CAE simulations. A business case analysis was conducted and showed promising results. One concept vehicle was built for the purpose of demonstrating concept feasibility. The paper also identifies areas for further development to enable such a vehicle to become a production reality at a later time.

In the early stages of a vehicle program, it is a common practice to set target ranges for the global body, suspension and powertrain modes. This modal management process allows engineers to avoid potential noise and vibration problems stemming from strong overlap of major global modes. Before the first prototype hardware is built, finite element models of the body, suspension and powertrain are usually exercised to compare predicted versus targeted ranges of the major system modes in the form of a modal management chart. However, uncertainty associated with the design parameters, manufacturing process and other sources can lead to a major departure from the design intent when the first hardware prototype is built. In this study, a first order reliability method is used to predict variance of the eigen values due to parameter uncertainties. This allows the CAE engineers to add a “three sigma” bound on the eigen values reported in the modal management chart.

Traditionally, vehicle emission testing has used non-intelligent analyzers to meet government-regulated standards. Typically, these instruments would provide a 0 to 5-volt signal to a central test cell computer which would then handle all calibrations including analyzer linearization, zero and span corrections, stability checks, time delays, and sample readings. Modern gas analyzers now contain intelligence within each individual analyzer; this has caused the calibration methods to change dramatically. New methods were developed in the bench control system to take advantage of the intelligence of the analyzers by creating a distributed control architecture. The zeroing, spanning, and linearization methods are quite different from the previous protocols. The results, however, will provide more accurate reading to be used in calculating vehicle emissions.

In automotive industry, all passenger vehicles are treated with damping materials to reduce structure borne noise. The effectiveness of damping treatments depends upon design parameters such as choice of damping materials, locations and size of the treatment. This paper proposes a CAE (Computer Aided Engineering) methodology based on finite element analysis to optimize damping treatments. The developed method uses modal strain-energy information of bare structural panels to identify flexible regions, which in turn facilitates optimization of damping treatments with respect to location and size. The efficacy of the method is demonstrated by optimizing damping treatment for a full-size pick-up truck. Moreover, simulated road noise performances of the truck with and without damping treatments are compared, which show the benefits of applying damping treatment.

As SULEV emission regulations approach, the bag mini-diluter (BMD) technology is gaining acceptance as a replacement for the existing constant volume sampler (CVS) for SULEV exhaust emission measurement and certification. The heart of the BMD system is the direct vehicle exhaust (DVE) flow measurement system. Due to the transient nature of vehicle exhaust during a standard FTP emission test cycle, the DVE must be capable of rapid and accurate response in order to track these varying exhaust flow rates. The DVE must also be robust enough to accurately measure flow rate despite variations in exhaust gas composition, pulsation effects, and rapid changes in both exhaust temperature and pressure. One of the primary DVE systems used on BMDs is the E-Flow, an ultrasonic flow meter manufactured by Flow Technologies, Inc.

A process to achieve vehicle system level NVH objectives using CAE simulation tools is discussed. Issues of modeling methodology, already covered adequately in the literature, are less emphasized so that the paper can focus on the application of a process that encompasses objective setting, design synthesis, and performance achievement using simulation predictions. A reference simulation model establishes correlation levels and modeling methods that are applied to future predictions. The new model, called a “Digital Mule”, is an early new product “design intent” simulation used to arrive at subsystem goals to meet the vehicle level NVH objectives. Subsystem goals are established at discrete noise paths where structure borne noise enters the body subsystem. The process also includes setting limits on the excitation sources, such as suspension and powertrain.

Today automotive thermal systems development is a joint effort between an OEM and its suppliers. This paper presents a pilot program showing how OEMs and suppliers can jointly develop a reliable and robust thermal system using CAE tools over the internet. Federated Intelligent Product Environment (FIPER) has been used to establish B2B communication between OEMs and suppliers. Suppliers remotely run thermal systems computer models at the OEM site using the FIPER B2B feature.

Springback study on a Dodge Ram fender outer panel is detailed in this paper. A simple measurement fixture is designed for the panel, wherein non-contact laser scan technology is applied The measurement data are compared with the original CAD design surface and deviation contour maps are obtained. Consistency of measurement is studied at different sections among three samples. Details of FEA simulations are outlined. The comparison between measurement and simulation prediction is summarized. A method to describe the consistency of measurement and the accuracy of simulation prediction is proposed. The targets for measurement consistency and simulation accuracy are verified. A sensitivity analysis is also performed to investigate various simulation input parameters.

It is becoming increasingly difficult to obtain good repeatability from running lab vehicle correlation testing, since vehicle variability is so significant at the Low ULEV and SULEV emissions levels. These new emission standards are becoming so stringent that it makes it very difficult to distinguish whether a problem is a result of vehicle variability, test cell sampling or the analytical system. A vehicle exhaust emission simulator (VEES) developed by Horiba, can simulate emissions from low emitting gasoline vehicles by producing tailpipe flow rates containing emissions constituents ( HC, CH4, CO, NOx, CO2 ) injected at the tailpipe flow stream via mass flow controllers.

As the standards for exhaust emissions have become more stringent, the quality control tools used to evaluate the performance of low level samplers and analyzers has become more important. The Vehicle Exhaust Emissions Simulator (VEES) was developed to evaluate the performance of vehicle or engine exhaust emissions sampling and analytical systems. The simulator emulates emissions from low-emitting gasoline vehicles by producing a simulated exhaust stream containing emission constituents (HC, CO, CO2, and NOx) injected via Mass Flow Controllers (MFCs). This paper discusses various applications of the VEES as a quality control tool for ULEV and SULEV testing. A comparison is made between the injected amount of exhaust species by the VEES and the amounts recovered by the different sampling systems. Different root cause scenarios are discussed as to the source of discrepancies between the results on the CVS and BMD for different driving cycles.